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IPMI
2009
Springer
14 years 8 months ago
Bayesian Registration via Local Image Regions: Information, Selection and Marginalization
We propose a novel Bayesian registration formulation in which image location is represented as a latent random variable. Location is marginalized to determine the maximum a priori ...
Matthew Toews, William M. Wells III
TNN
2010
205views Management» more  TNN 2010»
13 years 2 months ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu
RSFDGRC
2005
Springer
100views Data Mining» more  RSFDGRC 2005»
14 years 1 months ago
A Hybrid Approach to MR Imaging Segmentation Using Unsupervised Clustering and Approximate Reducts
Abstract. We introduce a hybrid approach to magnetic resonance image segmentation using unsupervised clustering and the rules derived from approximate decision reducts. We utilize ...
Sebastian Widz, Kenneth Revett, Dominik Slezak
CORR
2011
Springer
151views Education» more  CORR 2011»
13 years 2 months ago
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject’s behavior during a scanning se...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
ISBI
2008
IEEE
14 years 8 months ago
Mutual information-based feature selection enhances fMRI brain activity classification
In this paper, we adress the question of decoding cognitive information from functional Magnetic Resonance (MR) images using classification techniques. The main bottleneck for acc...
Bertrand Thirion, Cécilia Damon, Vincent Mi...